A Robust Position Estimation Method in the Integrated Navigation System via Factor Graph

被引:0
|
作者
Quan, Sihang [1 ]
Chen, Shaohua [2 ]
Zhou, Yilan [1 ]
Zhao, Shuai [1 ]
Hu, Huizhu [1 ,2 ]
Zhu, Qi [2 ]
机构
[1] Zhejiang Univ, State Key Lab Modern Opt Instrumentat, Hangzhou 310058, Peoples R China
[2] Zhejiang Lab, Inst Intelligent Percept, Hangzhou 311500, Peoples R China
基金
国家重点研发计划;
关键词
integrated navigation system; factor graph; robustness; GNSS outliers; INFORMATION FUSION; KALMAN FILTER;
D O I
10.3390/rs16030562
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Achieving higher accuracy and robustness stands as the central objective in the navigation field. In complex urban environments, the integrity of GNSS faces huge challenges and the performance of integrated navigation systems can be significantly affected. As the proportion of faulty measurements rises, it can result in both missed alarms and false positives. In this paper, a robust method based on factor graph is proposed to improve the performance of integrated navigation systems. We propose a detection method based on multi-conditional analysis to determine whether GNSS is anomalous or not. Moreover, the optimal weight of GNSS measurement is estimated under anomalous conditions to mitigate the impact of GNSS outliers. The proposed method is evaluated through real-world road tests, and the results show the positioning accuracy of the proposed method is improved by more than 60% and the missed alarm rate is reduced by 80% compared with the traditional algorithms.
引用
收藏
页数:23
相关论文
共 50 条
  • [21] A New Robust Filtering Method of GNSS/MINS Integrated System for Land Vehicle Navigation
    Xu, Tongxu
    Xu, Xiang
    Xu, Dacheng
    Zou, Zelan
    Zhao, Heming
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2022, 71 (11) : 11443 - 11453
  • [22] Collaborative navigation method based on adaptive time-varying factor graph
    Wang, H.
    Hu, L.
    Tao, J.
    AERONAUTICAL JOURNAL, 2025,
  • [23] A Study on Graph Optimization Method for GNSS/IMU Integrated Navigation System Based on Virtual Constraints
    Qiu, Haiyang
    Zhao, Yun
    Wang, Hui
    Wang, Lei
    SENSORS, 2024, 24 (13)
  • [24] A Robust INS/USBL/DVL Integrated Navigation Algorithm Using Graph Optimization
    Li, Peijuan
    Liu, Yiting
    Yan, Tingwu
    Yang, Shutao
    Li, Rui
    SENSORS, 2023, 23 (02)
  • [25] A low-cost integrated navigation system based on factor graph nonlinear optimization for autonomous flight
    Sina Taghizadeh
    Mohsen Nezhadshahbodaghi
    Reza Safabakhsh
    Mohammad Reza Mosavi
    GPS Solutions, 2022, 26
  • [26] A Novel Fusion Method for DR/GPS Integrated Navigation System
    Zhang, Santong
    Yang, Shiwu
    2008 6TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, VOLS 1-3, 2008, : 87 - 89
  • [27] INS/GPS integrated navigation uncertain system state estimation based on minimal variance robust filtering
    Wu, Zhou
    Shi, Hang
    Liu, Baosheng
    2006 IMACS: MULTICONFERENCE ON COMPUTATIONAL ENGINEERING IN SYSTEMS APPLICATIONS, VOLS 1 AND 2, 2006, : 631 - +
  • [28] A Factor Graph Optimization Method for High-Precision IMU-Based Navigation System
    Lyu, Pin
    Wang, Bingqing
    Lai, Jizhou
    Bai, Shiyu
    Liu, Ming
    Yu, Wenbin
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 72
  • [29] A Factor Graph Method for AUV Navigation in the Mobile Docking Progress
    Ruan, Liang
    Chen, Shumin
    Zhou, Jie
    Zeng, Daheng
    Xu, Yuanxin
    GLOBAL OCEANS 2020: SINGAPORE - U.S. GULF COAST, 2020,
  • [30] Preliminary Comparison of Kalman and Minimax Approaches to Error Estimation of Integrated Navigation System
    Fokin, Leonid A.
    Shiryaev, Vladimir I.
    2013 INTERNATIONAL SIBERIAN CONFERENCE ON CONTROL AND COMMUNICATIONS (SIBCON), 2013,